218Y Assignment 4
Lillian Wei Hung
2022/02/16
Improvement includes the following:
The depth-damage plotly for vehicle was revised.
A time plot of sum of AAL for Vehicle in the period of 2020~2050 was presented.
Monte Carlo simulation was revised.
A count of 0/1 vehicle households to be affected by floods was estimated according to the Monte Carlo simulation result.
PART I. Building risk estimation
7 selected census block groups in Redwood City
Redwood City in Block level of 7 selected census block groups
Max flood of 7 census block groups in Redwood City: For the maximum case out of 9 flood scenarios, slr=50, rp=100, the severe flooding areas are scattered in the central part of the region with one most severe place on the south boundary.
The buildings affected by the max flood are scattered in the center of the region with the flood depth mostly around 300~500 cm.
Vulnerability for building: The relation between depth and percent damage for building considered is as follows.
## depth perc_damage SD
## 1 -2 0.000 0.000
## 2 -1 0.025 0.027
## 3 0 0.134 0.020
## 4 1 0.233 0.016
## 5 2 0.321 0.016
## 6 3 0.401 0.018
## 7 4 0.471 0.019
## 8 5 0.532 0.020
## 9 6 0.586 0.021
## 10 7 0.632 0.022
## 11 8 0.672 0.023
## 12 9 0.705 0.024
## 13 10 0.732 0.027
## 14 11 0.754 0.030
## 15 12 0.772 0.033
## 16 13 0.785 0.037
## 17 14 0.795 0.041
## 18 15 0.802 0.045
## 19 16 0.807 0.049For annual flood, only when sea level rise reaches 50 cm, it may cause a bit over 1 feet average depth of building flood. For 1 in 20 years, as sea level rise reaches above 25 cm, the average depth of building flood can go beyond 1.5 feet. when sea level rise reaches 50 cm, it may cause a about 2.5 feet average depth of building flood. For 1 in 100 year, the average depth of building flood can go over 2 feet.
The Redwood city building damage for 1 in 100 year flood follows close to the relation between average flood depth and percent damage from the model in Table 1 of “Economic Guidance Memoranda”.
For annual flood, only when SLR reaches to 50 cm, it may cause some degree of building damage with damage percentage roughly 0.25. For 1 in 20 years, as sea level rise reaches above 25 cm, the building damage percentage due to flood may be over 0.25. when SLR reaches to 50 cm, it may cause some degree of building damage with damage percentage roughly 0.35. For 1 in 100 years, the vehicle damage percentage may go beyond 0.3.
## # A tibble: 10 x 10
## SLR `2020` `2030` `2040` `2050` `2060` `2070` `2080` `2090` `2100`
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 0 0.942 0.923 0.793 0.508 0.235 0.094 0.033 0.011 0.005
## 2 25 0 0.051 0.198 0.453 0.581 0.44 0.249 0.128 0.071
## 3 50 0 0 0.001 0.035 0.176 0.363 0.409 0.313 0.19
## 4 75 0 0 0 0 0.007 0.099 0.224 0.296 0.29
## 5 100 0 0 0 0 0 0.004 0.075 0.162 0.219
## 6 125 0 0 0 0 0 0 0.01 0.064 0.126
## 7 150 0 0 0 0 0 0 0 0.025 0.055
## 8 175 0 0 0 0 0 0 0 0.001 0.034
## 9 200 0 0 0 0 0 0 0 0 0.01
## 10 500 0 0 0 0 0 0 0 0 0## Simple feature collection with 7 features and 3 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -122.27 ymin: 37.51551 xmax: -122.2229 ymax: 37.55506
## Geodetic CRS: NAD83
## # A tibble: 7 x 4
## GEOID aal count geometry
## * <chr> <dbl> <int> <MULTIPOLYGON [°]>
## 1 060816103031 17663902. 360 (((-122.2428 37.54358, -122.2425 37.54361, -122.~
## 2 060816103032 22577189. 572 (((-122.2506 37.52618, -122.25 37.52667, -122.24~
## 3 060816103033 27169276. 319 (((-122.2468 37.53698, -122.2468 37.53699, -122.~
## 4 060816103034 25471587. 509 (((-122.2524 37.54451, -122.2508 37.54794, -122.~
## 5 060816103041 29722308. 573 (((-122.2553 37.52967, -122.2513 37.53291, -122.~
## 6 060816103042 28546981. 443 (((-122.27 37.52961, -122.27 37.52967, -122.2699~
## 7 060816103043 31856156. 332 (((-122.2685 37.52795, -122.2685 37.52796, -122.~The estimated total AAL for building damage is as follows:
## [1] "$183007397.748801"## [1] 3108The estimated AAL per building is as follows:
## [1] "$58882.6891083658"PART II. Vehicle risk estimation
The percent damage to Vehicle is based on the damage function from Table 3 of Economic Guidance Memorandum, 09-04, Generic Depth-Damage Relationships for Vehicles in 2009. All vehicles are assumed to be sedans.
For annual flood, only when sea level rise reaches 50 cm, it may cause average depth of flood about 1.25 feet. In every 20 year of frequency, as sea level rise reaches above 25 cm, the average depth of flood can go beyond 1.5 feet. As sea level rise reaches above 50 cm, the average depth of flood is about 2.5 feet. The average depth of flood can go beyound 2 ft. for every 100 years.
For annual flood, only when sea level rise reaches 50cm, the average percentage of vehicle damage is 0.35. For every 20 years, as sea level rise reaches above 25cm, the vehicle damage percentage is close to 0.4. As sea level rise reaches above 50 cm, the vehicle damage percentage is close to 0.5. The vehicle damage percentage may be close to 0.5 or over for every 100 years.
The trend between average flood depth and percent damage to vehicle is a pretty horizontal line which indicates really mild relation between average flood depth with percent damage to vehicle in Redwood City.
EMFAC growth rate 2030-2050 are as follows:
## [1] 1.062723## [1] 1.109196## [1] 1.142658The total AAL across years (2020~2050) was estimated through the EMFAC vehicle growth rates adjustment by multiplying the 2030, 2040, 2050 data by growth rate estimated from EMFAC 2030-2050.
The middle part in Redwood City region will suffer from the highest vehicle damage, followed by the mid-southern and northern parts.
## Simple feature collection with 7 features and 3 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -122.27 ymin: 37.51551 xmax: -122.2229 ymax: 37.55506
## Geodetic CRS: NAD83
## # A tibble: 7 x 4
## GEOID sum_aal count geometry
## * <chr> <dbl> <int> <MULTIPOLYGON [°]>
## 1 060816103031 513707. 360 (((-122.2428 37.54358, -122.2425 37.54361, -122.2~
## 2 060816103032 826867. 572 (((-122.2506 37.52618, -122.25 37.52667, -122.248~
## 3 060816103033 1349988. 319 (((-122.2468 37.53698, -122.2468 37.53699, -122.2~
## 4 060816103034 869564. 509 (((-122.2524 37.54451, -122.2508 37.54794, -122.2~
## 5 060816103041 1118083. 573 (((-122.2553 37.52967, -122.2513 37.53291, -122.2~
## 6 060816103042 748349. 443 (((-122.27 37.52961, -122.27 37.52967, -122.2699 ~
## 7 060816103043 211125. 332 (((-122.2685 37.52795, -122.2685 37.52796, -122.2~The total AAL from vehicle damage after vehicle growth rate adjustment is estimated as follows:
## [1] "$5637684.53022767"The AAL per building for vehicle damage after vehicle growth rate adjustment is estimated as follows:
## [1] "$1813.92681152756"Monte Carlo simulation for vehicle damage
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -2.000 1.347 2.025 2.011 2.674 9.762
The mean of vehicle damage from monte carlo simulation is as follows.
## [1] 2.024502The margin of error of vehicle damage from monte carlo simulation is as follows.
## [1] 0.000181681
## [1] 2.024684## [1] 2.0243290% confidence interval of average flood depth is (2.024322,2.024686).
## depth perc_damage SD
## 1 0.0 0.000 0.0100
## 2 0.5 0.076 0.0242
## 3 1.0 0.280 0.0184
## 4 2.0 0.462 0.0151
## 5 3.0 0.622 0.0145
## 6 4.0 0.760 0.0157
## 7 5.0 0.876 0.0174
## 8 6.0 0.970 0.0192
## 9 7.0 1.000 0.0206
## 10 8.0 1.000 0.0206
## 11 9.0 1.000 0.0206
## 12 10.0 1.000 0.020690% confidence interval of average flood depth is (2.024322,2.024686). According to the vehicle vulnerability model, the percent damage for depth 2 ft. will be 0.462. Therefore,a count of 0/1 vehicle households estimated to be affected by floods is as follow.
## # A tibble: 2 x 3
## vehicle_N estimate_sum count
## <dbl> <dbl> <dbl>
## 1 0 13927 6434
## 2 1 77532 35820Assumptions:
The vulnerability for building percent damage is based on the relation between average flood depth and percent damage in Table 1 of “Economic Guidance Memoranda”. The vulnerability for vehicle percent damage is based on the model in Table 3 of “Economic Guidance Memoranda”.
Vehicle counts in San Mateo County were collected from EMFAC that includes Redwood City for the years 2020, 2030, 2040, and 2050. Vehicle Categories, LDA (“Passenger Cars”) and LDT1 (“Light-Duty Trucks) were considered to estimate the numbers of vehicles in the period of 2020-2050. EMFAC Vehicle counts were used to estimate of the % increase in vehicles decade by decade and to adjust for the vehicle risk AAL for 2030, 2040, and 2050.
ACS 5-yr 2019 data about vehicle ownership in Redwood City were used for an estimate of the total number of owned vehicles in each census block group of Redwood City.
It is assumed that vehicles are distributed evenly across population and population is distributed evenly across buildings in a block.
Conclusions:
Annually the building may encounter roughly 1 feet depth of flood, but it only occurs as sea level rise reaches to 50 cm. Once in every 20~100 years, the building may expose to 1.5~2 feet floods as sea level rise go over 25 cm or over.
The building percent damage is about 0.25 annually as sea level rise reaches to 50 cm. Once in every 20~100 years, the building percent damage may go between 0.25~0.3 or over.
The total AAL across years (2020~2050) was estimated through the EMFAC vehicle growth rates adjustment by multiplying the middle 10 year AAL by 2030 growth rate, the following 10 years by 2040 growth rate, and the last 5 years by 2050 growth rate.
Based on the Monte Carlo simulation result, the 90% confidence interval of depth for vehicles are roughly (2.024322,2.024686) ft. According to the vehicle vulnerability model, the percent damage for depth 2 ft. will be 0.462. Therefore,a count of 0/1 vehicle households estimated to be affected by floods is 6434 and 35820, respectively.